Curriculum Vitae


Personal Details

  • Date of birth: September 5th, 1977
  • Place of birth: Sant Cugat del Vallès (Catalonia, Spain)
  • Nationality: Catalan
  • Present Citizenship: Spanish
  • Address: Dels Sarriera, 26, 17003 Girona, Catalonia, Spain
  • E-mail: pau.herrero{at}


  • 2000 - Industrial Engineering at University of Girona (Catalonia - Spain) (5 years). 
  • 2001 - Training course at THALES AIRBORNE SYSTEMS (France)  (1 year).
  • 2001 - Member of MiceLab Group at University of Girona (5 years).
  • 2002 - Participant of the European project CHEM (3 years).
  • 2006 - Ph.D. in Control Engineering at University of Girona and at University of Angers (France) (4 years).
  • 2007 - Postdoctoral stay at Doyle's Group (University of California - Santa Barbara) (1 year).
  • 2008-2010 - Researcher at the research group on Endocrinology and Diabetes of the Hospital de Sant Pau - Universitat Autònoma de Barcelona (EDUAB-HSP), and employed by the CIBER-BBN Network.

Current Working Position

  • I'm currently working as a research fellow at the Institute of Biomedical Engineering of Imperial College London.

Research Interests

  • The main focus of my research is on developing bio-inspired control algorithms in the context of a bio-inspired artificial pancreas project for the control of type 1 diabetes mellitus. The Wellcome Trust, the goal of which is to transfer this technology to initial trials and ultimately to real live, is currently funding this work.
  • Until today, control algorithms used in the context of an artificial pancreas have been mainly based on classical closed-loop control techniques like, Proportional Integral Derivative (PID) control and Model Predictive Control (MPC). Nevertheless, these techniques still need to demonstrate better performance before being implemented in a commercial artificial pancreas.
  • Recent developments of mathematical models of the β-cell physiology, which are able to describe the glucose-induced insulin release at a molecular level, have provided a new class of promising bio-inspired control algorithms, which can be potentially used in an artificial pancreas framework.
  • We are strongly convinced that trying to mimic the pancreatic β-cells functioning is the best way to achieve normoglycemia in subjects with T1DM.
  • In addition to this, I have ongoing research to create a fault detection system in order to supervise possible adverse events, such as glucose sensor failures and insulin infusion problems, occurring in the functioning of an artificial pancreas. This work is another indispensable piece of the puzzle towards a realistic realization of an artificial pancreas.
  • Another ongoing research that is under the focus of my interest is the development of a Decision Support System (DSS) for T1DM management based on Case Based Reasoning (CBR). CBR is a consolidated artificial intelligence technique, already successfully applied in medicine, that tries to solve newly encountered problems by applying the solutions learned from solving problems encountered in the past. This is similar to the way a human might solve a newly encountered problem. This DSS is intended to provide advices to the common situations a diabetic subject has to face, such as, meal related insulin doses, hyperglycemia and hypoglycemia, and is expected to be integrated in a telemedicine system already being developed by our group.